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Sustainability-based selection decisions for e-waste recycling operations

Author

Listed:
  • Yan Xu

    (Northwestern Polytechnical University
    Monash University)

  • Chung-Hsing Yeh

    (Monash University)

Abstract

Selecting operation alternatives for processing a recycling job is an important decision in managing e-waste recycling operations. This paper develops a novel approach to making selection decisions for e-waste recycling operations based on their sustainability performance under environmental, economic, and social dimensions. This approach addresses two new and important issues under a new selection problem structure. A job-oriented assessment method with a fuzzy knowledge base is constructed to address the first issue of how to consistently assess the performance of operation alternatives for a given recycling job with the precise or imprecise specification of the job attributes. A sustainability-based optimal weighting model is developed to address the second issue of how to determine optimal weighting for the three sustainability dimensions to reflect the company’s sustainability concerns and priorities under specific operational settings. With the assessment method and the optimal weighting model, the overall sustainability performance of each operation alternative for a given recycling job can be obtained, on which the selection decision can be made. To examine the effectiveness of the approach, an empirical study on an e-waste operation alternatives selection problem of an Australian e-recycler is conducted. The job-oriented sustainability-based selection approach significantly enhances the efficiency, consistency, and sustainability of processing e-waste recycling jobs.

Suggested Citation

  • Yan Xu & Chung-Hsing Yeh, 2017. "Sustainability-based selection decisions for e-waste recycling operations," Annals of Operations Research, Springer, vol. 248(1), pages 531-552, January.
    • Handle: RePEc:spr:annopr:v:248:y:2017:i:1:d:10.1007_s10479-016-2269-2
    DOI: 10.1007/s10479-016-2269-2
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